aweswitch

v0.1.4 safe
3.0
Low Risk

A tiny local launcher for switching AI agent runtime profiles.

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators across all checks, with no network calls, shell executions, or obfuscations detected. The metadata suggests a potential new maintainer but lacks other red flags.

  • No network calls detected
  • Single package from maintainer
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network interaction for its functionality.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or unauthorized access.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
  • Metadata: The maintainer has only one package, which may indicate a new or less active account, but there are no other red flags.

📦 Package Quality Overall: Low (3.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_aweswitch.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8237 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Peng" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aweswitch 
Create a command-line utility named 'ProfileJumper' using Python that leverages the 'aweswitch' package to manage different runtime profiles for AI agents. This utility should allow users to easily switch between various configurations and settings without needing to manually edit configuration files. Here’s a detailed plan on how to proceed:

1. **Setup Project Structure**: Start by setting up your project directory. Include necessary files such as `requirements.txt` for dependencies, `README.md` for documentation, and `main.py` as the main entry point of the application.

2. **Install Dependencies**: In `requirements.txt`, ensure you include 'aweswitch' and any other necessary packages like `click` for command-line interface enhancements.

3. **Define Profiles**: Create a JSON file to store different AI agent profiles. Each profile should contain unique settings and configurations relevant to an AI agent's operation. For example, profiles might differ based on the type of task (text generation, image processing), specific algorithms used, or even different API keys for accessing external services.

4. **Implement Profile Switching Mechanism**: Utilize the 'aweswitch' package to create a seamless way to load and switch between these profiles. Your implementation should allow users to activate a profile with a simple command, and 'aweswitch' should handle the loading of the appropriate configuration into the system's context.

5. **User Interface**: Develop a user-friendly CLI where users can list available profiles, select a profile to activate, and view details about the current active profile. Use 'click' to enhance the command-line experience.

6. **Security Considerations**: Since profiles may contain sensitive information such as API keys, implement basic security measures. Ensure that the JSON file storing profiles is not world-readable and consider encrypting sensitive data within the profiles.

7. **Testing and Documentation**: Write tests to ensure that profile switching works correctly under various scenarios. Document how to install and use 'ProfileJumper', including examples of common commands and how to add new profiles.

8. **Deployment**: Prepare 'ProfileJumper' for deployment. Package it as a standalone executable that users can download and run directly. Consider hosting the project on GitHub and providing instructions for installation via pip.

By following these steps, you will have developed a powerful yet simple tool for managing AI agent profiles, enhancing flexibility and ease-of-use for developers and AI enthusiasts.

💬 Discussion Feed

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